Triple

T32475958
Position Surface form Disambiguated ID Type / Status
Subject Decew Falls E829975 entity
Predicate watercourse P415 FINISHED
Object Beaverdams Creek
Beaverdams Creek is a small waterway in Ontario, Canada, known for flowing over Decew Falls near St. Catharines.
E2296152 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Beaverdams Creek | Statement: [Decew Falls, watercourse, Beaverdams Creek]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Beaverdams Creek
Triple: [Decew Falls, watercourse, Beaverdams Creek]
Generated description
Beaverdams Creek is a small waterway in Ontario, Canada, known for flowing over Decew Falls near St. Catharines.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3491ff3b48190b50a7fa00bb05b1f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c3913f108190b2e10106534b6392 completed May 3, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a823ecb03d48190b7ebe39166838312 completed Aug. 16, 2026, 10:50 p.m.
NEDg Description generation batch_6a823f5b50648190926c70afa9df7403 completed Aug. 16, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a823fad6c348190859edc774bc800ed completed Aug. 16, 2026, 10:54 p.m.
Created at: May 1, 2026, 12:58 a.m.